Algorithm for Outlier Detection in Large Dataset Based on Weighted KNN
一种基于加权KNN的大数据集下离群检测算法

Traditional KNN is an advanced algorithm based on the distance of outlicr detection algorithm on large data- set. However this algorithm only uses the k`h nearest neighbor as the criterion for outher which is inaccurate under cer- lain condition. This paper presented a weighted KNN outlier detection algorithm for large datasets. In this algorithm, a weight factor is presented. It represents the average distance of its k nearest neighbors. The outlicrs arc those having the largest distance with it's k`h neighbor and having the biggest weight under the same condition. The algorithm improves the accuracy of the outlicr detection algorithm. Experiment result shows that the algorithm is feasible compared with the traditional KNN.